Apparatus and method for optical tissue detection

ABSTRACT

Apparatus for optical tissue detection and discrimination between a tissue of a user and non-tissue materials and method of optical tissue detection and discrimination between a tissue of a user and non-tissue materials are provided. The apparatus for optical tissue detection includes one or more of light sources. The apparatus can further include at least one photodetector. A processor can be operable to determine whether the detected light is from a tissue of a user.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit of provisional application 62/217,679filed Sep. 11, 2015, said application is expressly incorporated byreference herein in its entirety.

FIELD

The present disclosure relates to an optical tissue detection apparatusand method for detecting a tissue using the optical tissue detectionapparatus.

BACKGROUND

Monitoring exertion via a heart rate monitor has long been a centerpieceof training for professional and performance athletes, as well asamateurs and retired players. Additional tests can be performed on theindividual and involve taking measurements of the individual by aprofessional. For example, some methods involve drawing of blood fromthe individual. Specifically, in order to measure lactate, theindividual has blood drawn and tests performed to determine the lactatein the blood at the specified time.

BRIEF DESCRIPTION OF THE DRAWINGS

Implementations of the present technology will now be described, by wayof example only, with reference to the attached figures. It is to benoted, however, that the appended drawings are not to be consideredlimiting scope of the present disclosure.

FIG. 1 is a schematic diagram optical-electronic sensor array operableto detect tissue according to the present disclosure;

FIG. 2A is a schematic diagram of a front of a non-invasiveoptical-electronic device according to the present disclosure;

FIG. 2B is a schematic diagram of the back of a non-invasiveoptical-electronic device according to the present disclosure;

FIG. 2C is a schematic diagram of a Near-InfraRed Spectroscopy (NIRS)sensor that is included on a non-invasive optical-electronic deviceaccording to the present disclosure;

FIG. 3 illustrates the components of an optical-electronic deviceaccording to the present disclosure;

FIG. 4A illustrates an environment within which the non-invasiveoptical-electronic device can be implemented, according to the presentdisclosure;

FIG. 4B illustrates another environment within which the non-invasiveoptical-electronic device can be implemented, according to the presentdisclosure;

FIG. 4C illustrates another environment within which the non-invasiveoptical-electronic device can be implemented, according to the presentdisclosure;

FIG. 5 is a flowchart describing an algorithm used to generatecalibration factors used to convert detected light data into opticaldensities, according to an example of this disclosure;

FIG. 6 is a flowchart describing a generic method of optical detectionof a tissue of a user;

FIG. 7A is a graph displaying raw analog to digital conversion (ADC)ambient light counts corresponding to optical data detected, during afirst trial, from tissues of a user and non-tissue materials;

FIG. 7B is a graph displaying the common logarithm of the optical data(D_(ijm)at a 15 mm LED to photodiode separation distance;

FIG. 7C is a graph displaying tissue detection signals derived fromoptical data detected during the first trial from the tissues of theuser and the non-tissue materials;

FIG. 7D is a graph displaying hydration indices (top), hemoglobinindices (middle), and hemoglobin concentration indices (bottom) derivedfrom optical data detected during the first trial from the tissues ofthe user and the non-tissue materials;

FIG. 7E is a graph displaying the common logarithm of the ADC countscorresponding to optical data detected from the tissues of the user andthe non-tissue materials of the first trial at a 27 mm LED to photodiodeseparation distance;

FIG. 8A is a graph displaying raw ADC ambient light counts correspondingto optical data detected during a second trial from tissues of a userand non-tissue materials;

FIG. 8B is a graph displaying the common logarithm of the optical data(D_(ijm)) at a 15 mm LED to photodiode separation distance;

FIG. 8C is a graph displaying tissue detection signals derived fromoptical data detected during the second trial from the tissues of theuser and the non-tissue materials;

FIG. 8D is a graph displaying hydration indices (top), hemoglobinindices (middle), and hemoglobin concentration indices (bottom) derivedfrom optical data detected during the second trial from the tissues ofthe user and the non-tissue materials;

FIG. 8E is a graph displaying the common logarithm of the ADC countscorresponding to optical data detected from the tissues of the user andthe non-tissue materials of the first trial at a 27 mm LED to photodiodeseparation distance;

FIG. 9A is a graph displaying raw ADC ambient light counts correspondingto optical data detected, during a third trial, from tissues of a userand non-tissue materials;

FIG. 9B is a graph displaying the common logarithm of the optical data(D_(ijm)) at a 15 mm LED to photodiode separation distance;

FIG. 9C is a graph displaying tissue detection signals derived fromoptical data detected during the third trial from the tissues of theuser and the non-tissue materials;

FIG. 9D is a graph displaying hydration indices (top), hemoglobinindices (middle), and hemoglobin concentration indices (bottom) derivedfrom optical data detected during the third trial from the tissues ofthe user and the non-tissue materials;

FIG. 9E is a graph displaying the common logarithm of the ADC countscorresponding to optical data detected from the tissues of the user andthe non-tissue materials of the third trial at a 27 mm LED to photodiodeseparation distance;

FIGS. 10A-I are graphs displaying the combined hydration index ratios(FIGS. 10A-C), hemoglobin index ratios (Hb fraction ratio, FIGS. 10D-F),and hemoglobin concentration index ratios (Hb conc. Ratio, FIGS. 10G-I)of the tissue and non-tissue materials from the first, second, andthird;

FIG. 11 is a graph displaying two ranges of hemoglobin index (y-axis)compiled from optical data of user profiles using an exemplarynon-invasive optical tissue detection device according to the disclosureherein;

FIG. 12 is a graph displaying two ranges of the hydration index (y-axis)compiled from optical data of the user profiles using an exemplarynon-invasive optical tissue detection device according to the disclosureherein;

FIG. 13 is a graph displaying two ranges of hemoglobin concentration(y-axis) compiled from optical data of the user profiles using anexemplary non-invasive optical tissue detection device according to thedisclosure herein;

FIG. 14 is a plot showing relative values of total hemoglobin (HbF,x-axis) and hemoglobin concentration index (HbConc, y-axis) with thedark circular region indicating the range of HbConc and HbF valuescorresponding to positive tissue detection; and

FIG. 15 is another plot showing relative values of total hemoglobin(HbF, x-axis) and hemoglobin concentration index (HbConc, y-axis) withthe dark rectangular region indicating the range of HbConc and HbFvalues corresponding to positive tissue detection.

DETAILED DESCRIPTION

Various examples of the disclosure are discussed in detail below. Whilespecific implementations are discussed, it should be understood thatthis is done for illustration purposes only. A person skilled in therelevant art will recognize that other components and configurations canbe used without parting from the spirit and scope of the disclosure.

It should be understood at the outset that although illustrativeimplementations of one or more examples are illustrated below, thedisclosed apparatus and method can be implemented using any number oftechniques. The disclosure should in no way be limited to theillustrative implementations, drawings, and techniques illustratedherein, but can be modified within the scope of the appended claimsalong with their full scope of equivalents.

Unless otherwise specified, any use of any form of the terms “connect,”“engage,” “couple,” “attach,” or any other term describing aninteraction between elements is not meant to limit the interaction todirect interaction between the elements and also can include indirectinteraction between the elements described. In the following discussionand in the claims, the terms “including” and “comprising” are used in anopen-ended fashion, and thus should be interpreted to mean “including,but not limited to . . . ”. The various characteristics described inmore detail below, will be readily apparent to those skilled in the artwith the aid of this disclosure upon reading the following detaileddescription, and by referring to the accompanying drawings. The term“substantially” is defined to be essentially conforming to theparticular dimension, shape or other word that substantially modifies,such that the component need not be exact. For example, substantiallycylindrical means that the object resembles a cylinder, but can have oneor more deviations from a true cylinder. The term “about” when used torefer to a range includes values that can be slightly above or below therange. For example, “about” can refer to the extension of the rangebased on the order of significant digits that are used. The use of theterm about does not require the range to extend beyond the valuesindicated, whereby there is explicit support for the range listed inexact values. The term “close” refers to the proximity of an object toanother object. This can be such that the objects almost or do touch atleast partially. In other examples, an object is close to another objectwhen there is no object between the two objects. In general, the termclose refers to a short distance, which is relative to the size of theobjects involved.

The present disclosure generally relates to a non-invasiveoptical-electronic device operable to determine the presence of atissue. A tissue as used herein refers to a group of biological cellsthat perform a similar function. In at least one example, thenon-invasive optical-electronic device can also be operable to determinea level of a biological indicator within tissue or blood vessels.Examples of non-invasive optical-electronic devices operable todetermine biological indicators are described in U.S. Pat. No. 8,996,088entitled APPARATUS AND METHOD FOR IMPROVING TRAINING THRESHOLD, theentire contents of which are incorporated herein by reference. Theoptical-electronic device can be used by itself or in combination withother optical-electronic devices or biosensors. The present non-invasivesensing devices can optionally be operable to detect physiologicalparameters, such as muscle tissue oxygenation parameters, concentrationof oxygenated hemoglobin, deoxygenated hemoglobin, and total hemoglobinconcentration, degree of hydration, and lactate concentration. Thepresent non-invasive sensing device can be implemented using NearInfraRed Spectroscopy (NIRS) as a radiation source. The presentnon-invasive sensing device can further include a detector configuredfor receiving NIRS signals and subsequent detection thereof. The presentdisclosure allows for tissue detection across a wide range of skincontact area. For example, the present disclosure allows for tissuedetection on a calf, head, thigh, arm, and the like.

FIG. 1 illustrates a non-invasive optical-electronic device 100,according to an example of the present disclosure. The device 100 can beplaced in direct contact with a portion of a user, such as a calf,wrist, forearm, or head. The device 100 can be placed and secured indirect contact with a portion of a user, such as a calf, wrist, forearm,or head. In at least one example, a strap, a sleeve, a wrap, a portionof an article of clothing such as a pant leg, a shirt sleeve, a jacket,a sock, a visor or hat, or any other suitable article of clothing canaffix the device 100 to the user. In other implementations, the device100 can be operable to receive touch or be held temporarily in contactwith a user or subject (user will be used throughout, but it includessubjects that may not be the direct user of the device). The device 100can alternatively be in the incorporated into an accessory article suchas a wrist watch, phone, phone case, waist belt, sweat bands, or anyother suitable accessory article for placement and securement in directcontact with a portion of a user. Additionally, the device 100 can beincorporated into other devices such a smart phone, a computer, a doorlock, a security entrance, a door panel, or any other device whereconfirmation of a user's presence or identity of a user is desirable.The device 100 can be used with an optional output device, such as asmartphone (as shown), a smart watch, computer, mobile phone, tablet, ageneric electronic processing and displaying unit, cloud storage, or aremote data repository via a cellular network or wireless Internetconnection.

The device 100 includes an optical photodetector 110 and opticalemitters 120, 140. In general, the device 100 uses two or more low-powerlasers, light emitting diodes (LEDs) or quasi-monochromatic lightsources as optical emitters 120, 140 and low-noise photodetectingelectronics, as optical photodetectors 110, to determine the opticalabsorption of chromophores, such as water, hemoglobin in its multipleforms, including oxyhemoglobin (HbO₂), deoxyhemoglobin (HHb),oxymyoglobin, deoxymyoglobin, cytochrome c, lipids, melanins, lactate,glucose, myoglobin (including myoglobin at least one of oxymyoglobin,deoxymyoglobin, and total myoglobin) or metabolites. The metabolites caninclude at least one of lactate and lactic acid. Cytochrome c can beused, for example, to track muscle adaptation to training. In anotherexample, the device 100 can use a broad-spectrum optical source, such asa light emitter 120, and a photodetector, such as the opticalphotodetector 110, that is sensitive to the spectral components oflight, such as a spectrometer, or a charge-coupled device (CCD) or otherlinear photodetector coupled with near-infrared optical filters. Asknown to those skilled in the art, photodetectors 110 and light emitters120 and 140 may be interchangeable without loss of generality. Also,multiple light emitters and light detectors can be used.

The optical-electronic device 100 can be operable to to include a sensor(not shown) operable to measure photoplethysmography (PPT) of the user.The sensor can include a corresponding optical emitter (not shown) and acorresponding optical photodetector (not shown). The device 100 can alsoinclude a second sensor (not shown) operable to measureelectrocardiography (EKG) and derived systolic time intervals (STI) ofthe user. The second sensor can include a corresponding first electrode(not shown) and a corresponding second electrode (not shown). Theoptical-electronic device 100 can optionally include a processor that isoperable to analyze data generated by the device 100 to determine acardiac response to exercise and the supply, arteriovenous difference,utilization of oxygen by the muscle tissue and hydration of the musculartissue. In other examples, the processor can be a part of a largerdevice and the optical-electronic device 100.

The device 100 can include a power supply, such as a battery, to supplypower to the sensors and other components in the device 100. In oneexample, the device 100 has a skin contact area of 3.5″×2″. In anotherexample, the device 100 has a skin contact area of 35 mm×35 mm. Thepresent technology can be implemented in a package that is just largeenough to accommodate the desired spacing between the at least oneemitter and the at least one detector.

In at least one example, the processor is operable to determinebiological indicators, including, but not limited to a relativepercentage, a saturation level, an absolute concentration, a rate ofchange, an index relative to a training threshold, and a threshold. Inother cases, the processor is operable to determine perfusioncharacteristics such as pulsatile rhythm, blood volume, vascular tone,muscle tone, and angiogenesis from total hemoglobin and watermeasurements.

In at least one example, the processor is operable to discriminatebetween biological indicators and non-biological indicators. Theprocessor is at least first operable to determine the presence ofbiological tissue. As indicated above, the issue can be human skin,mammalian skin or plant tissue, such as vegetables, legumes or fruits.In other examples, the tissue can be a particular type of tissue such asmuscle tissue and epithelial tissue. When the presence of tissue isdetected, the device can be operable to launch an activity. For example,the activity can be initiating data collection, unlocking an electronicdevice, transmitting data to a remote location, or other activity thatcan be used by an electronic device on which the sensors are located ora remote electronic device. In one example, if it is determined that thedevice 100 is in contact with a tissue of the user, the photodetector110 will initiate data collection. The data collection can be based uponthe desired characteristics that are being measured. The collection ofdata can, for example, be raw analog to digital conversion light countscorresponding to luminous radiations backscattered from the chromophoresin a tissue of a user or in non-tissue material. From the collecteddata, an absolute level of the oxygenated hemoglobin concentration(HbO₂) and reduced hemoglobin (HHb), and corresponding total hemoglobinconcentration, hemoglobin index and hydration index, can be calculatedthat enables the oxygenation/saturation of a tissue to be established,among other determinations as described herein. Other physiologicaltraits of the user can be observed from the collected data such as, forexample, the cadence, pace, and heart rate. If, however, it isdetermined that the device 100 is in contact with a non-tissue material,the photodetector 110 will not make measurements and device 100 could,for example, alert the user to check device placement. The determinationcan be made by a processor of the device 100, which contains opticaldata indicative of tissues of one or more users and non-tissuematerials.

FIGS. 2A-2C illustrates a non-invasive optical-electronic device 200,according to an alternative example of the present disclosure. Asmentioned above, the optical-electronic device can be incorporated intoanother device or article of clothing. The device 200 can be operable tobe worn on a limb of a user as described above with respect to device100. In at least one example, the device 200 can be optimized to a givenlimb for increased accuracy. In other examples, the device 200 can beoptimized based on the size, gender, or age of the user. In still otherexamples, a variety of the above optimizations can be implemented for agiven device. FIG. 2A illustrates the front of the optical-electronicdevice. FIG. 2B illustrates the back of the optical-electronic device,including emitters 220, 230, 250 and photodetector 210. The device 200also includes data and charging contacts 270. In at least one example,the data and charging contacts 270 can be used to electrically detect ifthe sensor is making contact with the skin of a user. The presence ofmultiple emitters 220, 230, 250 on the optical-electronic device allowsfor spatially-resolved data gathering in real-time. Theoptical-electronic device 200 can be operable to determine the opticalabsorption of chromophores, such as water, hemoglobin in its multipleforms, including oxyhemoglobin (HbO₂), deoxyhemoglobin (HHb),oxymyoglobin, deoxymyoglobin, cytochrome c, lipids, melanins, lactate,glucose, or metabolites.

FIG. 2C illustrates a NIRS sensor that can be included on thenon-invasive optical-electronic device 200, according to an example ofthe disclosure. As shown in FIG. 2C, the NIRS sensor includes lightemitters 280 and 281 which emit light that is scattered and partiallyabsorbed by the tissue. Each emitter 280, 281 can be operable to emit asingle wavelength of light or a single range of wavelengths. In at leastone example, each emitter 280, 281 can be operable to emit at leastthree wavelengths of light or at least three ranges of wavelengths. Eachemitter 280, 281 can include one or more light emitting diodes (LEDs).Each emitter 280, 281 can include a low-powered laser, LED, or aquasi-monochromatic light source, or any combination thereof. Eachemitter 280, 281 can also include a light filter.

A fraction of the light emitted by emitters 280 and 281 is detected byphotodetector 285, as illustrated by the parabolic or “banana shaped”light arcs 291 and 292. As the symmetry of the light arcs indicate, thedirection of light propagation does not matter. That is, emitter andphotodetector locations are interchangeable and, hence, photodetectorscould be replaced with light emitters, and vice-versa. Emitters 280,281, are separated by a known distance 290 and produce a signal that islater detected at photodetector 285. The detected signal is used toestimate the effective attenuation and absorption coefficients of theunderlying tissue as described later in FIG. 6, for example at blocks640 and 650. In at least one example, the known distance 290 is 12 mm.In at least one example, the known distance 290 is 15 mm. In at leastone example, the known distance 290 is 27 mm. In other examples, theknown distance can be selected based on a variety of factors, which caninclude the wavelength of the light, the tissue involved, the body massindex of the user or the age of the user.

The optical-electronic device 200 disclosed herein can have differentnumbers of emitters and photodetectors without departing from theprinciples of the present disclosure. Further, the emitters andphotodetectors can be interchanged without departing from the principlesof the present disclosure. Additionally, the wavelengths produced by theLEDs can be the same for each emitter or can be different.

In at least one example, the device 200 is used for the monitoring ofphysiological parameters of a user during a physical activity orroutine. Use of the device 200 is particularly relevant in endurancetype sports, such as running, cycling, multi-sport competition, rowing,but can also be used in other physical activities. The device 200 can beoperable to wirelessly measure real-time muscle parameters duringphysical exercise. The device 200 can be secured to a selected musclegroup of the user, such as the leg muscles of the vastus lateralis orgastrocnemius, which are primary muscle groups of running and cycling.

FIG. 3 illustrates the components of an optical-electronic device 300according to an example of the present disclosure. As shown in FIG. 3,the optical-electronic device includes one or more emitters 310 and oneor more photodetectors 320, which are coupled to a processor 330. Theprocessor 330 is coupled to a non-transitory storage medium 340. Thedevice 300 is coupled to an output device 390.

The one or more emitters 310 delivers light to the tissue and the one ormore photodetectors 320 collect the optically attenuated signal that isback-scattered from the tissue. In at least one example, the one or moreemitters 310 can be operable to emit at least three separate wavelengthsof light. In another example, the one or more emitters 310 can beoperable to emit at least three separate bands or ranges of wavelengths.In at least one example, the one or more emitters 310 can include one ormore light emitting diodes (LEDs). The one or more emitters 310 can alsoinclude a light filter. The one or more emitters 310 can include alow-powered laser, LED, a quasi-monochromatic light source, or anycombination thereof. The one or more emitters 310 can emit light rangingfrom infrared to ultraviolet light. As indicated above, the presentdisclosure uses NIRS as a primary example and the other types of lightcan be implemented in other examples and the description as it relatesto NIRS does not limit the present disclosure in any way to prevent theuse of the other wavelengths of light. In another example, the one ormore emitters 310 emit light in the range from 600 nanometers to about1100 nanometers, a range that is transmitted relatively well by tissuebut which includes significant absorption by hemoglobin in the lowerrange and by water in the higher range, allowing improved detection ofthese chromophores.

The data generated by the one or more photodetectors 320 can beprocessed by the processor 330, such as a computer processor, accordingto instructions stored in the non-transitory storage medium 340 coupledto the processor. The processed data can be communicated to the outputdevice 390 for storage or display to a user. The displayed processeddata can be manipulated by the user using control buttons or touchscreen controls on the output device 390.

The optical-electronic device 300 can include an alert module 350operable to generate an alert. The processor 330 can send the alert tothe output device 390 or the alert module 350 can send the alertdirectly to the output device 390. In at least one example, theoptical-electronic device 300 can be configured so that the processor330 is capable of sending an alert to the output device 390 without thedevice including an alert module 350.

The alert can provide notice to a user, via a speaker or display on theoutput device 390, of a change in biological indicator conditions orother parameter being monitored by the device 300, or the alert can beused to provide an updated biological indicator level to a user. In atleast one example, the alert can be manifested as an auditory signal, avisual signal, a vibratory signal, or combinations thereof. In at leastone example, an alert can be sent by the processor 330 when apredetermined biological indicator event occurs during a physicalactivity. In at least one example, an alert can be sent by the processor330 when a non-biological indicator event, obtained for example from anon-tissue material, occurs during a physical activity or that theoptical-electronic device 300 has not been in contact with the user fora predefined period of time.

In at least one example, the optical-electronic device 300 can include aGlobal Positioning System (GPS) module 360 capable of determininggeographic position and tagging the biological indicator data withlocation-specific information. The optical-electronic device 300 canalso include a thermistor 370 and an inertial measurement unit (IMU)380. The inertial measurement unit (IMU) 380 can be used to measure, forexample, gait performance of a runner or pedal kinematics of a cyclist,as well as physiological parameters of a user during a physical activityor routine. The thermistor 370 and inertial measurement unit (IMU) 380can also serve as independent sensors capable of independently measuringparameters of physiological threshold. The thermistor 370 and inertialmeasurement unit (IMU) 380 can also be used in further algorithms toprocess or filter the optical signal.

FIG. 4A illustrates one example of an environment within which thenon-invasive optical-electronic device 400 a can be implemented,according to an example of the present disclosure. As shown in FIG. 4A,the optical-electronic device 400 a is worn by a user to determinebiological indicator levels during a physical activity or routine. Theoptical-electronic device 400 a is depicted as being worn on the calf ofa user 405; however, the optical-electronic device 400 can be worn onany portion of the user suitable for monitoring biological indicatorlevels. The device 400 a can be used with an output device 410, such asa smartphone (as shown), a smart watch, computer, mobile phone, tablet,a generic electronic processing and displaying unit, cloud storage, or aremote data repository via a cellular network or wireless Internetconnection.

As shown in FIG. 4A, the optical-electronic device 400 a, communicateswith an output device 410 a so that data collected by theoptical-electronic device 400 a is displayed or transferred to theoutput device 410 for communication of real-time biological indicatordata to the user 405 a. In FIG. 4A, the optical-electronic device 400 ais incorporated in a calf sleeve for direct contact with the calf of auser. In at least one example, an alert can be communicated from thedevice 400 to the output device 410 so that the user 405 can be notifiedof a biological indicator event. In at least one example, an alert canbe communicated from the device 400 a to the output device 410 so thatthe user 405 can be notified of a non-biological indicator event or thatthe optical-electronic device 400 has not been in contact with the userfor a predefined period of time. Communication between the device 400 aand the output device 410 can be via a wireless technology, such asBLUETOOTH®, infrared technology, or radio technology, or can be througha wired connection. Transfer of data between the optical-electronicdevice 400 and the output device 410 can also be via removable storagemedia, such as a secure digital (SD) card. In at least one example, ageneric display unit can be substituted for the output device 410.

The optical-electronic device 400 a also communicates with a personalcomputing device 440 or other device capable of storing or displayinguser-specific biological indicator data. The personal computing device440 can include a desktop computer, laptop computer, tablet, smartphone,smart watch, or other similar device. Communication between the device400 and the personal computing device 440 can be via a wirelesstechnology, such as BLUETOOTH®, infrared technology, or radiotechnology. In other examples, the communication between the device 400and the personal computing device 440 can be through a wired or otherphysical connection. Transfer of data between the optical-electronicdevice 400 and the personal computing device 440 can also be viaremovable storage media, such as an SD card.

The output device 410 can communicate with a server 430 via a network420, allowing transfer of user-specific biological indicator data to theserver 430. The output device 410 can also communicate user-specificbiological indicator data to cloud-based computer services orcloud-based data clusters via the network 420. The output device 410 canalso synchronize user-specific biological indicator data with a personalcomputing device 440 or other device capable of storing or displayinguser-specific biological indicator data. The output device 410 can alsosynchronize user-specific biological indicator data with a personalcomputing device 440 or other device capable of both storing anddisplaying user-specific biological indicator data. Alternatively, thepersonal computing device 440 can receive data from a server 430 orcloud-based computing service via the network 420.

The personal computing device 440 can communicate with a server 430 viaa network 420, allowing the transfer of user-specific biologicalindicator data to the server 430. The personal computing device 440 canalso communicate user-specific biological indicator data to cloud-basedcomputer services or cloud-based data clusters via the network 420. Thepersonal computing device 440 can also synchronize user-specificbiological indicator data with the output device 410 or other devicecapable of storing or displaying user-specific biological indicatordata.

The optical-electronic device 400 a can also directly communicate datavia the network 420 to a server 430 or cloud-based computing and datastorage service. In at least one example, the device 400 can include aGPS module capable of communicating with GPS satellites (not shown) toobtain geographic position information.

The optical-electronic device 400 a can be used by itself or incombination with other optical-electronic devices or biosensors. Forexample, the optical-electronic device 400 a can be used in combinationwith heart rate (HR) biosensor devices, foot pod biosensor devices,and/or power meter biosensor devices. The optical-electronic device 400a can also be used in combination with ANT+™ wireless technology anddevices that use ANT+™ wireless technology. The optical- electronicdevice 400 a can be used to aggregate data collected by other biosensorsincluding data collected by devices that use ANT+™ technologies.Aggregation of the biosensor data can be via a wireless technology, suchas BLUETOOTH®, infrared technology, or radio technology, or can bethrough a wired connection.

The biosensor data aggregated by the optical-electronic device 400 a canbe communicated via a network 420 to a server 430 or to cloud-basedcomputer services or cloud-based data clusters. The aggregated biosensordata can also be communicated from the optical-electronic device 400 ato the output device 410 or personal computing device 440.

In at least one example, the optical-electronic device 400 a can employmachine learning algorithms by comparing data collected in real-timewith data for the same user previously stored on a server 430, outputdevice 410, or in a cloud-based storage service. The machine learningalgorithm can also be performed on or by any one of the output device410, cloud-based computer service, server 430, or personal computingdevice 440, or any combination thereof.

FIG. 4B illustrates an example of an environment within which anon-invasive optical-electronic device 400 b can be implemented,according to an example of the present disclosure. Theoptical-electronic device 400 b is substantially similar to theoptical-electronic device 400 a except that the optical-electronicdevice 400 b is incorporated in a head band for direct contact with thehead of a user. While the illustration includes a headband, the presentdisclosure includes implementation in other devices or objects worn onthe head such as eyewear, glasses, contact lenses, headphones, earplugs, virtual reality devices. Other examples can be worn around theneck as well. In some implementations, the device can be operable toinclude a display device that allows for visual data to be displayed tothe user.

FIG. 4C illustrates an example of an environment within which anon-invasive optical-electronic device 400 c can be implemented,according to an example of the present disclosure. Theoptical-electronic device 400 c is substantially similar to theoptical-electronic device 400 a and 400 b except that theoptical-electronic device 400 b is incorporated in a wrist watch fordirect contact with the wrist of a user. In at least one example, thewrist watch can be a smart watch, and can be an output device 411 whichis substantially similar in function to output device 410. In otherexamples, the wrist watch can be implemented with a limited display andlimited processing capability. In yet other examples, theoptical-electronic device 400 c can be incorporated in a wrist band.

According to the present disclosure, determination of the level of abiological indicator within tissue or blood vessels is achieved bycalculating a relative match, or indices, between the spectral datareceived at the photodetector with a predetermined spectral data set ofone or more chromophores corresponding to the biological indicator. Inat least one example, the predetermined spectral data set corresponds tothe signal spectra of specific analyses that can be readily obtainedfrom the literature. See for example, Analyt. Biochem. Vol. 227, pp.54-68 (1995). The relative match calculation is performed by calculatinga projection of the spectral data set captured from a user in thedirection of the predetermined spectral data set in order to calculatean index that reflects the proximity of the match. The spectralprojection method can be used to calculate a relative percentage levelof a biological indicator or, with proper calibration, can be used tocalculate the absolute concentration of a biological indicator.

The spectral projection method of determining the level of a biologicalindicator can be implemented mathematically using the inner productmethod which will be explained, by way of example, using the TOI as thebiological indicator of interest. TOI is the ratio of the oxygenatedhemoglobin (HbO₂) to total hemoglobin (tHb), where total hemoglobin(tHb) is equal to the combined concentrations of the oxygenatedhemoglobin (HbO₂) and the chromophore deoxygenated hemoglobin (HHb):

-   TOI=[HbO₂]/[tHb] or TOI %=100*([HbO₂]/[tHb]), where    [THb]=[HbO₂]+[HHb].

TOI, as used herein, includes the more specific parameter, SmO2, whichis the muscle oxygen saturation. SmO2 can also be the tissue oxygensaturation determined from optical measurements of muscle tissue. Bothoxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (HHb) arechromophores for which a spectral data set can be predetermined. Thenotation O(D) can be used to denote the predetermined spectral data foroxyhemoglobin (deoxyhemoglobin) at the same wavelengths for which thespectral data set for a user was measured at the photodetector, and Ucan be used to denote the measured data set, including an effectiveattenuation (μ_(eff)) or an effective absorption coefficient (μ_(a)).The inner product method of calculating the spectral projection can becalculated according to different mathematical methods, including, butnot limited to, a direction cosine method, vector projection method, anda pseudo-inverse projection method.

Direction Cosine Method:

${{TOI} = \frac{\left\langle {U,O} \right\rangle}{\left\langle {U,{O + {D\sqrt{\frac{\left\langle {O,O} \right\rangle}{\left\langle {D,D} \right\rangle}}}}} \right\rangle}},$

Vector Projection Method:

${{TOI} = \frac{\left\langle {U,O} \right\rangle}{\left\langle {U,{O + {D\frac{\left\langle {O,O} \right\rangle}{\left\langle {D,D} \right\rangle}}}} \right\rangle}},$

Pseudo-Inverse Projection Method:

${TOI} = {\frac{\left\langle {U,{O - {\frac{\left\langle {O,D} \right\rangle}{\left\langle {D,D} \right\rangle}D}}} \right\rangle}{\left\langle {U,{{O\left\lbrack {1 - \frac{\left\langle {O,D} \right\rangle}{\left\langle {D,D} \right\rangle}} \right\rbrack} + {D\left\lbrack {\frac{\left\langle {O,O} \right\rangle}{\left\langle {D,D} \right\rangle} - \frac{\left\langle {O,D} \right\rangle}{\left\langle {D,D} \right\rangle}} \right\rbrack}}} \right\rangle}.}$

All of these methods can be rewritten as

${TOI} = \frac{\left\langle {U,{O - {aD}}} \right\rangle}{\left\langle {U,{{O\left( {1 - a} \right)} + {D\left( {b - a} \right)}}} \right\rangle}$

-   where a and b are scalars defined as

$\begin{matrix}{{a = 0},{{b = \sqrt{\frac{\left\langle {O,O} \right\rangle}{\left\langle {D,D} \right\rangle}}};}} & \left. i \right) \\{{{a = 0},{{b = \frac{\left\langle {O,O} \right\rangle}{\left\langle {D,D} \right\rangle}};}}{and}} & \left. {ii} \right) \\{{a = \frac{\left\langle {O,D} \right\rangle}{\left\langle {D,D} \right\rangle}}{and}{b = \frac{\left\langle {O,D} \right\rangle}{\left\langle {D,D} \right\rangle}}} & \left. {iii} \right)\end{matrix}$

-   for the cosine, vector projection and pseudo-inverse methods,    respectively.

Prior to calculating indices, calibration coefficients can be generatedwhich allow the indices calculation to be corrected for the absorptionproperties of the tissue. FIG. 5 is a flowchart describing an algorithmused to generate the calibration coefficients that can be used, forexample, by the projection indices algorithm.

Referring to FIG. 5, a flowchart is presented in accordance with anexample. The example method shown in FIG. 5 is provided by way of anexample, as there are a variety of ways to carry out the method. Eachblock shown in FIG. 5 represents one or more processes, methods, orsubroutines, carried out in the example method shown in FIG. 5.Furthermore, the illustrated order of blocks is illustrative only andthe order of the blocks can change according to the present disclosure.Additional blocks can be added or fewer blocks can be utilized, withoutdeparting from the present disclosure.

The example calibration method can begin at block 500. At block 510, anyone of the above described the optical-electronic devices is attached toa phantom with known absorbances OD_(jm). The above procedure isrepeated for each spacing (m) at block 520 and for each LED (j) at block530. At block 540, all currents (i) are swept. At block 550, light dataD_(ijm) are captured. The calibration factors are calculated at block560, using the formula: C_(ijm)=10^(ODjm)/D_(ijm). Block 570 determineswhether the calibrations algorithm has been repeated for each LEDemitter. If the calibration has not been performed for one or more LEDemitters the blocks beginning with block 540 are repeated for theadditional LED until all LEDs have been calibrated. Block 575 determineswhether the calibration has been performed for all distances. If it isdetermined that calibration has not been performed for all distances,the blocks beginning with block 530 are repeated until the last LED andlast distance has been calibrated, upon which the calibration factorsare stored in block 580. Calibration factors C_(ijm) are stored on aserver and/or the firmware in block 585. The calibration algorithm iscompleted in block 590. The calibration factors stored according to thealgorithm described in FIG. 5 can be used, for example, by theprojection indices algorithm shown in FIG. 6.

Referring to FIG. 6, a flowchart is presented in accordance with anexample. The example method shown in FIG. 6 is provided by way of anexample, as there are a variety of ways to carry out the method. Eachblock shown in FIG. 6 represents one or more processes, methods, orsubroutines, carried out in the example method shown in FIG. 6.Furthermore, the illustrated order of blocks is illustrative only andthe order of the blocks can change according to the present disclosure.Additional blocks can be added or fewer blocks can be utilized, withoutdeparting from the present disclosure.

FIG. 6 describes an exemplary method of optical detection of a tissue ofa user and discrimination between the tissue of the user and non-tissuematerials. The method can determine whether the device 100, 200, 300 isin contact with a tissue of a user or in contact with a non-tissuematerial. The device 100, 200, 300 starts from an off position, or,alternatively, a sleep mode. The example algorithm can begin at block600. At block 600 the device 100, 200, 300 turns on (or activates) uponthe detection of a wake motion of the device 100, 200, 300. The wake upmotion can be for example a movement or motion of the device 100, 200,300. Alternatively, the device can turn on incrementally orperiodically, in block 600, in lieu of a motion or movement of thedevice 100, 200, 300. The period or increment of time can be anysuitable periodic or incremental amount of time. For example, fiveseconds. In other examples, the device can send a signal to a coupleddevice. The coupled device can be a watch or smart phone that is coupledwired or wirelessly to the the device. The signal can be a hardwareinterrupt.

At block 605, the detected light data D_(jm) is received by the devicefor a given current (i). Upon activating, the device 100, 200, 300 willgenerate and emit, using the corresponding optical emitters, radiationof at least three different wavelengths for irradiating a materialsurface which is in the path of the emitted radiation. In at least oneexample, at least one of the at least three different wavelengths cancorrespond to one of HbO₂, HHb or water. The device 100, 200, 300 willthen detect, using the corresponding optical photodetector, theoptically attenuated signal back-scattered from the material. The device100, 200, 300 will detect data over a predetermined period of time at apredetermined sampling rate. In block 605, the predetermined timerperiod is two seconds. The device 100, 200, 300 can alternatively detectdata over a time period ranging from 0.1 to 10 seconds, alternatively0.5 to 5 seconds, and alternatively 1 to 3 seconds. The device candetect data over a predetermined sampling rate of 0.1 to 10 Hz,alternatively 0.5 to 10 Hz, alternatively, 1 to 10 Hz, alternatively, 2to 8 Hz, alternatively, 4 to 6 Hz, and alternatively 5 Hz.

The detected light data are converted into optical densities for a givencurrent i using the calibration factors C_(jm), at block 610, using theequation: OD_(jm)=log₁₀(C_(ijm)×D_(ijm)). At block 615, a time-averageof OD_(jm) is determined. At block 620, the optical densities areconverted to effective attenuations, using the equation:μ_(eff)(j)=0.192(OD_(j2)-OD_(j1))−0.098. At block 625, the effectiveattenuations are converted to absorption coefficients, according to theequation:) μ_(a)(j)=0.5[sqrt(μ_(s)′(j)²+4/3μ_(eff)(j)²)−μ_(s)′(j)] whereμ_(s)′(j) is the reduced scattering coefficient for tissue beingmonitored, taken from, for example, from Applied Optics, Vol. 36, No. 1,pp. 386-396 (1997). The inner product is calculated at block 630,according to the equation: P_(k)=Σ_(j)μ_(a)(j)Finv_(jk), where Finv_(jk)is the pseudo-inverse of the known absorption spectra of chromophores(k), wherein k=1 for oxyhemoglobin, k=2 for deoxyhemoglobin and k=3 forwater, at wavelengths (j), and Σ_(j) denotes summation over index (j).At block 635, the HbF and pH₂O (that is, the percentage of water in thetissue) values are extracted from P_(k), according to the equationsHbF=P₁+P₂ and pH₂O=P₃. At block 640, the hemoglobin concentration index[HbConc] is determined, according to the formula HbConc=(5e4 * HbF/pH₂O.At block 645, parameter errors are calculated, according to thefollowing equations HbFError=(HbF-HbFTarget)/(HbFMAX-HbFMIN), andHbConcError=(HbConc-HbConcTarget)/(HbConcMAX-HbConcMIN). Constant valuesHbFTarget and HbConcTarget are given by HbFTarget=(HbFMAX+HbFMIN)/2 andHbConcTarget =(HbConcMAX+HbConcMIN)/2, as displayed in blocks 647 and649, respectively. If the HbF is greater than a minimum threshold valueand less than a maximum threshold value, and the HbConc is greater thana minimum threshold value and less than a maximum threshold value, thena determination that the photodetector is directed to a tissue of a useris made as described below, and further data collection is performed andthe data is collected for use in exercise analysis. In at least oneexample, the hemoglobin concentration index minimum threshold value(HbConcMIN) is 4.47. In at least one example, the hemoglobinconcentration index maximum threshold value (HbConcMAX) is 40.16. In atleast one example, the HbF minimum threshold value (HbFMIN) is 2.30e-5.In at least one example, the HbF maximum threshold value (HbFMAX)) is2.54e-4.

At block 650, an Error Value is calculated according to the equation:Error Value=sqrt(HbFError{circumflex over ( )}2+HbConcError{circumflexover ( )}2). At block 655, the error value is compared to a set errorvalue of 0.5. If the error value obtained in block 650 is less than 0.5,a determination is made at block 660 that a tissue of a user is detectedand subsequently enters a Daily Activity State, as shown in block 670.If the error value obtained in block 650 is greater than 0.5, adetermination is made at block 680 that a non-tissue material isdetected.

In block 670, the device 100, 200, 300 will continue to generate andemit, using the corresponding optical emitters, radiation of at leasttwo different wavelengths until a tissue is no longer detected or untila predetermined period of time has passed as done in blocks 685 and 690,respectively.

In block 685, upon determination in block 680 that a non-tissuematerial, the method will repeat, starting at block 605, for an allottedamount of time. As shown in block 685, the allotted time can be a 30second time period. The allotted time can be up to, for example, 5seconds, alternatively 10 seconds, alternatively 15 seconds,alternatively 30 seconds, and alternatively 60 seconds. In block 690, ifafter the allotted time period no tissue has been detected, the devicewill enter an idle state. The idle state can be an off position or asleep mode as described above or any other idle state which reducespower consumption.

In another example the error values HbConcError and HbFError arelinearly transformed and translated before their Euclidian distance tothe origin is calculated, wherein the translation is given bysubtraction by the mean value of HbConc and HbF parameters measured froma set X of known tissue measurements, and the linear transformation isgiven by matrix multiplication of the vector [HbConcError HbFError] withΛ^(−1/2)U^(T), wherein Λ and U are the eigenvalue and eigenvectormatrices of the covariance matrix of X.

As described above, the devices 100, 200, 300 can be used for the studyof muscle tissue oxygenation during exercise. The application of thepresent technology is particularly relevant in endurance type sports,such as running, cycling, multisport competition, rowing, etc., but canalso be successfully applied to other types of exercises and trainingmethods. The devices 100, 200, 300 can be operable to wirelessly measurereal-time muscle parameters during physical exercise. The devices 100,200, 300 can be secured to a selected muscle group of the user, such asthe leg muscles of the vastus lateralis or gastrocnemius, as describedabove (See FIG. 4A) which are primary muscle groups of running andcycling.

Muscle tissues increase their oxygen requirements during periods ofincreased stress (e.g. athletic activity). The more a muscle is beingstressed the more oxygen is extracted from arterial blood to supplythese needs. Therefore an appreciable desaturation of hemoglobin occursin stressed muscles, which correlates with exercise intensity. At thesame time, at rest and under steady-state exercise conditions, there isa balance between blood lactate production and its subsequent removal.As the muscles are stressed to greater and greater degrees more lacticacid is also produced as a byproduct. At a certain point (unique to eachuser) the body begins producing more lactic acid than it can remove. TheLT refers to the intensity of exercise at which there is an abruptincrease in blood lactate levels above baseline. Coaches and trainersuse the LT pace to generate training programs (frequently referred to aszone training) that are a combination of high volume low intensity,maximal steady-state, and supra-threshold interval workouts to improveathletic performance. LT training is one way to improve athleticperformance of the user.

During an exercise routine, which can comprise, for example, running,cycling, or swimming stages, or any other stage of an exercise routine,the devices 100, 200, 300 can, as described above, determine whether thedevices 100, 200, 300 are in contact with a tissue of a user asdescribed above, in contact with a non-tissue material, or in contactwith both, to determine whether to obtain data for exercise analysis.The optical-electronic devices 100, 200, 300, as disclosed herein, canalso transmit a signal or an alert to an output device such as a userdisplay or mobile device. One form of an alert can signal or flag theexistence of non-tissue materials which interfere with theidentification and/or determination of one or more biologicalindicators. The existence of non-tissue materials can be indicated bydetermining the relative match of a spectral data set representative ofreceived light and the null space for a matrix containing the spectrarepresentative of a predetermined data set of one or more chromophores,which is the set of vectors that will be mapped to 0 by the F matrix. Asdescribed at Step 650 of FIG. 6, the inner product is calculated asP_(k)=Σ_(j)μ_(a)(j)Finv_(jk), where P_(k) are the projections due toanalyte k, and Finv is the pseudo-inverse of matrix F containing thespectra of the analytes at wavelengths (j). The residual signal R isgiven by R=μ_(a)−P*F^(T), where T denotes the transpose and * denotesmatrix multiplication. Accordingly, R represents the part of thedetected signal that failed to project towards any of the analytes ofinterest. Under normal conditions, R remains low. However, under specialconditions, such as when clothing interferes with the optical-electronicdevice, an abrupt increase in the modulus of R would be expected. Whenthe modulus of R increases suddenly, or when it surpasses apre-determined threshold, an alarm can be conveyed to the user.Accordingly, the optical-electronic device can be operable to generate anull-space or residual signal to flag the existence of non-tissuematerials, including, but not limited to: tabletops, textiles, fabrics,plastics, polymeric materials, cellulosic materials, or other similarnon-tissue materials.

The method described in FIG. 6 of using the device 100, 200, 300 caninclude placing the optical photodetector and optical emitters incontact with the tissue to be analyzed, and starting the measuring cycleby using an appropriate signal. The method can also include the step ofemitting luminous radiations from the optical emitters at a givenoptical intensity and at least at three different wavelengths in thenear-infrared spectrum, where at least one is correspondent to a waterabsorption peak, in particular 980 nm, for a localized illumination ofthe tissue. Further, the method can include detecting the opticalintensity of the luminous radiations backscattered from the tissue usingthe optical photodetector at a set distance from the illuminated zoneand transforming the backscattered radiation detected in low noiseelectric signal. The method can further include calculating the absoluteconcentrations of oxygenated and deoxygenated hemoglobin, according tothe photon diffusion equation using the absorption coefficientspreviously calculated, and the step of calculating the absoluteconcentration of total hemoglobin as a sum of the oxygenated hemoglobinand deoxygenated hemoglobin concentrations and the oxygenation index ofthe tissue as the ratio of the oxygenated hemoglobin concentration overthe total hemoglobin concentration.

Additionally, the method can include displaying the data on theelectronic device. The steps for collecting, processing, analyzing, andcalculating information from the photodetector can be implemented incomputer programs using standard programming techniques. The programcode is applied to data generated by the photodetector to perform thefunctions described herein and generate output information NIRSvariables (e.g., physiological parameters). Each such computer programcan be stored on the processor in the photodetector or machine readablestorage medium (for example, CD ROM, hard drive, or flash drive) thatwhen read by the processor or other computer machines can cause theprocessor in the photodetector to perform the analysis and controlfunctions described herein.

In at least one example the tissue detection of block 660 signal can befurther used to determine whether the device is in continuous contactwith tissue, issuing an alarm whenever the device is determined to beout of contact with tissue for an allotted amount of time. The alarm canbe visual or audible in nature, or any other suitable means for alarmingthe user. The allotted time can be for example, 5 seconds, alternatively10 seconds, alternatively 15 seconds, alternatively 30 seconds, andalternatively 60 seconds. The allotted time can be, more particularly,30 seconds.

In at least another example the tissue detection signal is further usedto determine whether a specific user is trying to activate the device.Here, the user tissue data is first enrolled (measured) during anenrollment phase, in which multiple readings from multiple locations inthe user body are captured, thus creating a new and personalized rangeof thresholds to be used. That is, a personalized set of HbFMIN, HbFMAX,HbConcMIN, HbConcMAX values. Then, during tissue detection theuser-specific thresholds are used, resulting in a tissue detectionfunction more specific for that user while also rejecting a fraction ofother users and better rejecting non-tissue materials.

Experimental Results

To test the ability of the device 200 to discriminate between tissue ofa user and non-tissue materials, tissue detection trials were performedusing the device 200 on body parts of a user comprising tissue andnon-tissue materials. In a first, a second and a third trial describedbelow, data was obtained using the following procedure under roomlighting of approximately 1 candela. First, the device 200 was placed indirect contact with a body part of a user. Optical data was collectedfor 60 seconds. After the 60 second period, the device 200 was moved toanother body part or non-tissue material, depending on the trial, andoptical data (D_(ijm)) was collected for 60 seconds. The period of datacollection and transferring to another body part or non-tissue materialwas continued until all body parts and non-tissue materials were tested.After optical data was collected for the last non-tissue material, thedata collected for all body parts and non-tissue materials weretabulated for comparison. Irradiation of the samples and data collectionand analysis were performed as previously described.

In the first trial, using the device 200, tissue detection trials wereperformed, in the following order, on the left calf and left forearm ofa user, as the tissue sources, and on a black lycra sleeve, a gray lycrasleeve, a ream of white paper, a dark wooden table, a light coloredcarpet, a phone LCD screen, a phone cover, a roll of toilet paper, afront portion of a heart rate monitor, and back portion of a heart ratemonitor.

In the second trial, using the device 200, tissue detection trials wereperformed, in the following order, on the left calf of a user, a formicatable top, a dry towel, a humid towel, and a wet towel, a lens of a pairof swim goggles, a dry lycra swimsuit, a wet lycra swimsuit, a rubberfin, a rubber swim cap, and a clear plastic bag containing a wetswimsuit therein.

In the third trial, using the device 200, tissue detection trials wereperformed, in the following order, on the left calf of a user, the rightcalf of the user, the right forearm of the user, the palm of the righthand of the user, a white laminate tabletop, the interior of a backpack,the interior of a canvas bag, a rubber shoe sole, a transparent waterbottle having water therein, a foam headphone, and the wrapper of a foodbar.

FIG. 7A is a graph displaying raw ADC ambient light counts correspondingto optical data detected, during the first trial, from tissues of a userand non-tissue materials. Signal spikes correspond with the movement ofthe device 200 from one tissue to another, one tissue to a non-tissuematerial, or from one non-tissue material to another, since thephotodetector gets exposed to ambient light during movement. The firstsignal spike corresponds to the movement of the device 200 from the leftcalf of a user to the left forearm of the user, the second spikecorresponds to the movement of the device 200 from the left forearm ofthe user to a black lycra sleeve, the third spike corresponds to themovement of the device 200 from the black lycra sleeve to a gray lycrasleeve, the fourth spike corresponds to the movement of the device 200from the gray lycra sleeve to a ream of white paper, the fifth spikecorresponds to the movement of the device 200 from the ream of whitepaper to a dark wooden table, the sixth spike corresponds to themovement of the device 200 from the dark wooden table to a light-coloredcarpet, the seventh spike corresponds to the movement of the device 200from the light-colored carpet to a phone LCD screen, the eighth spikecorresponds to the movement of the device 200 from the phone LCD screento a phone cover, the ninth spike corresponds to the movement of thedevice 200 from the phone cover to a roll of toilet paper, the tenthspike corresponds to the movement of the device 200 from the roll oftoilet paper to a front portion of a heart rate monitor, and theeleventh spike corresponds to the movement of the device 100 from thefront portion of a heart rate monitor to a back portion of a heart ratemonitor.

FIG. 7B is a graph displaying the common logarithm of the optical data(D_(ijm)) at an LED-to-photo detector spacing of 15 mm. The data wasobtained when the first optical emitter and optical photodetector areseparated by a distance of fifteen millimeters (mm) (7A) and the secondoptical emitter and optical photodetector are separated by a distance of27 mm (7E). As indicated above, the spacing can be adjusted and is notconsidered limiting on the present disclosure. As with previous data,signal spikes correspond with the movement of the device 200 from onetissue to another, one tissue to a non-tissue material, or from onenon-tissue material to another. From the obtained optical data, μ_(a)and P_(k)(t) of each tissue and non-tissue material were calculated andHbF and HbConc were determined.

FIG. 7C is a graph displaying tissue detection signals derived fromoptical data detected during the first trial from the tissues of theuser and the non-tissue materials. As with previous data, signal spikescorrespond with the movement of the device 200 from one tissue toanother, one tissue to a non-tissue material, or from one non-tissuematerial to another. A horizontal line having a Tissue Detection Signalvalue of less than 0.5 corresponds to either a tissue or non-tissuematerial which is a false positive, as described above. A TissueDetection signal of less than 0.5 corresponds to a tissue having ahemoglobin index value and a hemoglobin concentration value in a rangeas described in references to FIGS. 11 and 13 respectively.

FIG. 7D is a graph displaying hydration indices (top), hemoglobinindices (middle), and hemoglobin concentration indices (bottom) derivedfrom optical data detected during the first trial from the tissues ofthe user and the non-tissue materials, showing that non-tissue materialsgenerally have HbF and HbConc values that vary from those described byFIGS. 11 and 13.

FIG. 7E is a graph displaying the common logarithm of the ADC countscorresponding to optical data (D_(ijm)) detected from the tissues of theuser and the non-tissue materials of the first trial, wherein theoptical emitter and optical photodetector are separated by a distance oftwenty-seven mm. As with previous data, signal spikes correspond withthe movement of the device 200 from one tissue to another, one tissue toa non-tissue material, or from one non-tissue material to another.

FIG. 8A is a graph displaying raw ADC ambient light counts. Signalspikes correspond with the movement of the device 200 from one tissue toanother, one tissue to a non-tissue material, or from one non-tissuematerial to another. The first signal spike corresponds to the movementof the device 200 from the left calf of a user to a formica tabletop,the second spike corresponds to the movement of the device 200 from theformica tabletop to a dry towel, the third spike corresponds to themovement of the device 200 from the dry towel to a damp towel, thefourth spike corresponds to the movement of the device 200 from the damptowel to a very wet towel, the fifth spike corresponds to the movementof the device 200 from the very wet towel to a lens of a pair of swimgoggles, the sixth spike corresponds to the movement of the device 200from the lens of a pair of swim goggles to a dry lycra swimsuit, theseventh spike corresponds to the movement of the device 200 from the drylycra swimsuit to a wet lycra swimsuit, the eighth spike corresponds tothe movement of the device 200 from the wet lycra swimsuit to a rubberfin, the ninth spike corresponds to the movement of the device 200 fromthe rubber fin to a rubber swim cap, and the tenth spike corresponds tothe movement of the device 200 from the rubber swim cap to a plastic bagcontaining a wet swimsuit.

FIG. 8B is a graph displaying the common logarithm of the optical data(D_(ijm).). As with previous data, signal spikes correspond with themovement of the device 200 from one tissue to another, one tissue to anon-tissue material, or from one non-tissue material to another. Fromthe obtained optical data, μ_(a) and P_(k)(t) of each tissue andnon-tissue material were calculated and HbF and HbConc were determined.

FIG. 8C is a graph displaying tissue detection signals derived fromoptical data detected during the second trial from the tissues of theuser and the non-tissue materials. As with previous data, signal spikescorrespond with the movement of the device 200 from one tissue toanother, one tissue to a non-tissue material, or from one non-tissuematerial to another.

FIG. 8D is a graph displaying hydration indices (top), hemoglobinindices (middle), and hemoglobin concentration indices (bottom) derivedfrom optical data detected during the second trial from the tissues ofthe user and the non-tissue materials.

FIG. 8E is a graph displaying the common logarithm of the ADC countscorresponding to optical data (D_(ijm)) detected from the tissues of theuser and the non-tissue materials of the first trial wherein the opticalemitter and optical photodetector are separated by a distance oftwenty-seven mm.

FIG. 9A is a graph displaying raw ADC ambient light counts correspondingto optical data detected, during the third trial, from tissues of a userand non-tissue materials wherein the optical emitter and opticalphotodetector are separated by a distance of fifteen millimeters (mm).Signal spikes correspond with the movement of the device 200 from onetissue to another, one tissue to a non-tissue material, or from onenon-tissue material to another. The first signal spike corresponds tothe movement of the device 200 from the left calf of a user to the rightcalf of the user, the second spike corresponds to the movement of thedevice 200 from the right calf of the user to the right forearm of theuser, the third spike corresponds to the movement of the device 200 fromthe right forearm of the user to the palm of the right hand of the user,the fourth spike corresponds to the movement of the device 200 from thepalm of the right hand of the user to a white laminate tabletop, thefifth spike corresponds to the movement of the device 200 from the whitelaminate tabletop to an interior of a backpack, the sixth spikecorresponds to the movement of the device 200 from the interior of thebackpack to a an interior of a canvas bag, the seventh spike correspondsto the movement of the device 200 from the interior of the canvas bag toa rubber shoe sole, the eighth spike corresponds to the movement of thedevice 200 from the rubber shoe sole to a transparent bottle filledwater, the ninth spike corresponds to the movement of the device 200from the transparent bottle filled water to a foam headphone, and thetenth spike corresponds to the movement of the device 200 from the foamheadphone to a wrapper of a food bar.

FIG. 9B is a graph displaying the common logarithm of the optical data(D_(ijm)). As with previous data, signal spikes correspond with themovement of the device 200 from one tissue to another, one tissue to anon-tissue material, or from one non-tissue material to another. Fromthe obtained optical data, μ_(a) and P_(k)(t) of each tissue andnon-tissue material were calculated and HbF and HbConc were determined.

FIG. 9C is a graph displaying tissue detection signals derived fromoptical data detected during the third trial from the tissues of theuser and the non-tissue materials. As with previous data, signal spikescorrespond with the movement of the device 200 from one tissue toanother, one tissue to a non-tissue material, or from one non-tissuematerial to another.

FIG. 9D is a graph displaying hydration indices (top), hemoglobinindices (middle), and hemoglobin concentration indices (bottom) derivedfrom optical data detected during the third trial from the tissues ofthe user and the non-tissue materials.

FIG. 9E is a graph displaying the common logarithm of the ADC countscorresponding to optical data detected from the tissues of the user andthe non-tissue materials of the third trial wherein the optical emitterand optical photodetector are separated by a distance of twenty-sevenmm. As with the previous data, signal spikes correspond with themovement of the device 200 from one tissue to another, one tissue to anon-tissue material, or from one non-tissue material to another.

FIGS. 10A-I are graphs displaying the combined hydration index ratios(FIGS. 10A-C), hemoglobin index ratios (HbF ratio, FIGS. 10D-F), andhemoglobin concentration index ratios (HbConc Ratio, FIGS. 10G-I) of thetissue and non-tissue materials from the first trial (FIGS. 10A, 10D,10G), second trial (FIGS. 10B, 10E, 10H), and third trial (FIGS. 10C,10F, 10I). Optical tissue detection thresholds are shown as in eachgraph as dashed purple lines. Non-tissue materials that weremisidentified as tissue using the individual threshold values arelabeled in red. As can be seen, non-tissue materials that generate alarge amount of light, such as a phone LCD screen, or contain moisture,such as a damp or wet towel, are potential sources of false positivesduring optical tissue detection using device 200. As with previous data,signal spikes correspond with the movement of the device 200 from onetissue to another, one tissue to a non-tissue material, or from onenon-tissue material to another. The graphs in FIGS. 10A-I allow fordetermination that HbConc and HbF parameters are sufficient to classifymaterials as tissue or non-tissue, since their combination resulted inthe lowest false-positive rate (only the swim cap was incorrectlyidentified as tissue when HbConc and HbF signals are taken intoaccount), and also to conclude that including the hydration index datawould not further improve the classification task.

In at least one example, the devices 100, 200, 300 can generate andcollect optical tissue data for more than one user. When the devices100, 200, 300 can generate and collect optical tissue data for more thanone user, the devices 100, 200, 300 can further use the optical tissuedata of each user to generate a corresponding profile for each user. Togenerate a profile of each user of the device 100, 200, 300 thefollowing method can be implemented.

First each user of the device 100, 200, 300 can create a user account ina non-transitory computer-readable storage medium located in theelectronic device and in a non-transitory computer-readable storagemedium located in the device 100, 200, 300. The user account can containinformation such as, for example, the name of the user, the age, heightand weight of the user, the home and billing address of the user, thee-mail address of the user, the phone number of the user, and othersimilar user account information. The non-transitory computer-readablestorage mediums store information regarding user and optical tissue dataof the user generated and collected during exercise routines and cancommunicate the information from the device 100, 200, 300 to theelectronic device as described above. Second, each user can perform Nroutines, where N is a number of times a routine is performed by theuser. The routines can be exercise routines. The exercise routines canbe, for example, one of running, cycling, swimming, strength training,hiking, or any other suitable exercise routine. Further, the exerciseroutines can be specific training routines. The specific trainingroutines can be, for example, cardiovascular training routines,endurance training routines, zone training, or any other suitabletraining routine. In each of N exercise and/or training routines,optical tissue data corresponding to any one or more of oxygenatedhemoglobin concentration, deoxygenated hemoglobin concentration, totalhemoglobin concentration, hemoglobin index, hemoglobin concentrationindex, hydration index, lactate threshold, and ventilatory threshold isgenerated and collected and communicated between the device 100, 200,300 and electronic device as described above. Upon reaching N routines,the optical tissue data can be analyzed and used by a processor, underinstruction of the non-transitory computer-readable storage mediumlocated in the electronic device, to generate a user profile. The userprofile is associated with the user account and the tissue data can befurther associated with user characteristics (age, gender, height,weight, etc). In at least one example, N is greater than 1.Alternatively, N is greater than 5, alternatively, greater than 10,alternatively greater than 20. Alternatively, the user profile can begenerated after every routine is performed and corresponding datagenerated, collected, and analyzed.

The device 100, 200, 300 and electronic device can further assigngenerated, collected and analyzed optical tissue from a routine to aspecific user profile without prior input identifying the user as thesource of the optical tissue data. Here, the electronic device cancompare the optical tissue data generated, collected and analyzed from aroutine and compare it to each user profile. Upon comparison of theroutine data to each user profile by the either or both of thenon-transitory computer-readable storage medium located in theelectronic device and in the non-transitory computer-readable storagemedium located in the device 100, 200, 300, the data associated withthat routine can be assigned to the user based on the similarity betweenthe routine data and the user profile. Such correlation of data from asingle routine data and the stored user profiles can thereby create abiometric recognition process because each user can have a distinct userprofile can on the user's individual optical tissue data generated,collected, and analyzed over N routines.

An example of a user profile assessment of six hundred ten (610) userprofiles is described below with respect to FIGS. 11-13. The data usedto generate FIGS. 11-13 was obtained using the following procedure withdevice 200. As stated above, the data illustrated in FIGS. 13-15 wasgenerated from data corresponding to the 610 individual user profiles,each user profile constituting a data set. For each user profile dataset, optical tissue data, as described above, was calculated during thefirst 35 seconds (“Start”) of a routine and at the 3.6 minute mark(“End”) of a user routine. The whiskers of the plotted boxplots shown inFIGS. 11-13 are then used to determine the HbConc and HbF thresholdvalues. These correspond to the fences of the aggregate data set,resulting in a 99.3% sensitivity to optical tissue and a false positiverate of 7.4%. That is, the device 200 is shown to have a 99.3%sensitivity to tissue detection and only 7.4% of the data can beattributed to non-tissue materials. As known to those skilled in theart, the upper fence of a data set is given by the third quartile of thedata set plus 1.5 times the interquartile range, while the lower fenceis given by the first quartile minus 1.5 times the interquartile range.

The threshold values are determined as follows: HbFMIN is given by thelower fence (whisker) of HbFStart shown in FIG. 11 and HbFMAX is givenby the higher fence (whisker) of HbFStart. HbConcMIN is given by thelower fence (whisker) of HbConcStart shown in FIG. 13 and HbConcMAX isgiven by the higher fence (whisker) of HbConcStart. The End values(HbFEnd and HbConcEnd) are shown for comparison, allowing one to confirmthat the parameter fence values do not vary greatly from the start tothe end of activities. Nevertheless, the start values were preferredgiven that tissue detection is expected to be most useful in thebeginning of an activity, as a method to determine that the device isattached to tissue and, thus, ready to start data collection.

In FIG. 11, a graph displaying two ranges of hemoglobin index (y-axis)compiled from optical data of the 610 user profiles at Start and at Endis shown. As can be seen, the Start and End range data do notappreciably change, but does slightly increase from Start to End. As canbe seen the 610 user profiles generated hemoglobin index range have alower “whisker” of 2.30e-5 and an upper whisker of 2.54e-4. Numericanalysis of the data further reveal that the hemoglobin index has avalue of 1.86e-4 in the top 1-percentile and 2.32e-4 in the top99-percentile at Start.

For a whisker of length w. The default is a w of 1.5. Points are drawnas outliers if they are larger than q3+w(q3−q1), wherein q3 correspondsto the third quartile and q1 corresponds to the first quartile, orsmaller than q1−w(q3−q1), where q1 and q3 are the 25th and 75thpercentiles, respectively. The default of 1.5 corresponds toapproximately +/−2.7σ and 99.3% coverage assuming a normal datadistribution. The plotted whisker extends to the adjacent value, whichis considered to be the most extreme data value that is would beindicative of a tissue of a user. Using the upper and lower whiskers asthe threshold corresponding to accepting approximately 99.3% of userdata as tissue, and those outside the whisker range are considered to benon-tissue material(s). In the case of individual users, tissue data canbe used from that user alone. Using tissue data from a single user mayresult in a tighter range between top and bottom whiskers for bothparameters for the individual user. In one example for one user, thetighter ranges were 9.0e-5<HbF<2.1E-4, and 18.4<HbConc<37.8. Whiskerranges can also be used for biometric recognition or identification ofuser data.

In FIG. 12, a graph displaying two ranges of hydration index (y-axis)compiled from optical data of the 610 user profiles at Start and at Endis shown. As can be seen, the Start and End range data do notappreciably change, but does slightly increase from Start to End. As canbe seen, the 610 user profiles generated hydration index range having alower “whisker” of 1.85×10⁻¹ and an upper whisker of 4.59×10 ⁻¹. Numericanalysis of the data further reveals that the hydration index has avalue of 2.19×10⁻¹ in the top 1-percentile and 3.32 x 10⁻¹ in the top99-percentile at Start.

In FIG. 13, a graph displaying two ranges of hemoglobin concentration(y-axis) compiled from optical data of the 610 user profiles at Startand at End is shown. As can be seen, the Start and End range data do notappreciably change, but does slightly increase from Start to End. As canbe seen the 610 user profiles generated hemoglobin concentration indexrange having a lower “whisker” of 4.47 and an upper whisker of 40.16Numeric analysis of the data further reveals that the hemoglobinconcentration index has a value of 28.39 in the top 1-percentile and49.57 in the top 99-percentile at START.

In each of FIGS. 11-13, compilation of the optical data of the 610 userprofiles generated a broad data value distribution. It should be noted,however, that each individual user profile would have corresponding datathat is distinct within the ranges outlined above. Because each userprofile will have a distinct data range corresponding to optical tissuedata from a corresponding set of N routines, each user can be comparedto the range of other users and can be discriminated from other users.Such discrimination between users can allow for determination of whichuser generated to the optical tissue data and thus allow for biometricrecognition of each individual user. Such discrimination can also resultin an improved ability to distinguish a given user from non-tissuematerial, reducing the false-positive rate and, thus, improve thespecificity of the device.

FIGS. 14 and 15 are plots showing relative values of total hemoglobinconcentration (HbF, x-axis) and hemoglobin concentration index (HbConc,y-axis) indicative of optical data obtained from a tissue of a user. InFIG. 16, the dark ellipsis comprises a range of total hemoglobinconcentration and hemoglobin concentration index values indicative of atissue using the rule by which tissue is detected when the Error value,given by sqrt(HbFError{circumflex over ( )}2+HbConcError{circumflex over( )}2), is larger than 0.5. The point at which the horizontal andvertical line passing through the dark ellipsis meet denotes the center(or target) of tissue detection bands (HbF=HbFTarget andHbConc=HbConcTarget) as previously described.

In FIG. 15, the dark rectangle comprises a range of total hemoglobinconcentration and hemoglobin concentration index values indicative of atissue using the rule by which tissue is detected whenHbConcMIN<HbConc<HbConcMAX and HbFMIN<HbF<HbFMAX. The point at which thehorizontal and vertical line passing through the dark rectangle meetdenotes the center (or target) of tissue detection bands (HbF=HbFTargetand HbConc=HbConcTarget) as previously described.

In another example the error values HbConcError and HbFError aretranslated by the estimated mean values of HbConc and HbF, respectively,and linearly-transformed by matrix multiplication with A^(−1/2)U^(T),the eigenvalue and eigenvector matrices of the covariance matrix of X.These linear operations corresponds to transforming the ellipsis of FIG.14 into a circle centered at the origin of the coordinate system, withthe benefit of allowing us to set an error function (and boundaryconditions) better capable to distinguishing between tissue andnon-tissue materials, further improving the specificity and sensitivityof the device 100, 200 and 300.

What is claimed is:
 1. An apparatus operable to optically detect tissue,the apparatus comprising: at least one light source operable to emitlight of at least three wavelengths into a material, at least one of theat least three wavelengths being about 980 nanometers; at least onephotodetector operable to detect at least a portion of the lightreflected from the material; a non-transitory medium coupled with aprocessor and storing instructions for determining whether the materialis a biological tissue of a subject or a non-tissue material and forlaunching an activity when the material is the biological tissue; andthe processor coupled with the at least one light source and the atleast one photodetector, the processor operable to execute theinstructions, stored in the non-transitory medium, for: determiningwhether the material is the biological tissue or the non-tissue materialbased on the light detected by the at least one photodetector, when thematerial is the biological tissue, launching the activity, wherein theactivity includes the at least one photodetector recording measurements,and the non-transitory medium is operable to store the recordedmeasurements, and when the material is the non-tissue material, notlaunching the activity, and initiating an alert by an output device tocheck placement of the apparatus, wherein the at least one light sourceemits light at predetermined intervals to determine if the at least onephotodetector is proximate to the tissue, and wherein the at least onelight source and the at least one photodetector are operable to beenabled by further activation, wherein the further activation includesthe processor detecting a movement.
 2. The apparatus of claim 1, whereinthe at least one light source emits light in at least three wavelengthsbetween about 600 nanometers to about 1100 nanometers.
 3. The apparatusof claim 1, wherein the at least one light source is coupled to anarticle of clothing that is operable to secure the at least one lightsource to a body part of the subject.
 4. The apparatus of claim 1,further comprising a transmitter that is operable to transmit the storedmeasurements to an electronic device.
 5. The apparatus of claim 1,wherein the processor is further operable to determine the subject froma plurality of previously identified subjects based on the detectedlight.
 6. The apparatus of claim 1, wherein the processor is furtheroperable to filter optical signals that do not correspond to detectedlight from the tissue of the subject.
 7. The apparatus of claim 6,wherein the filtered optical signals correspond to light emitted fromany one or more of plastics, polymeric materials, fabrics, textiles,non-tissue surfaces, or cellulosic materials.
 8. The apparatus of claim1, wherein the at least one light source, the at least one photodetectorand the processor are coupled to an article of clothing that comprisesone of a strap, sleeve, jacket, wrist strap, glass, hat, cap, helmet orwrap configured for securement to a body part of the subjectcorresponding to the tissue of the subject.
 9. The apparatus of claim 1,wherein the at least one light source is a light emitting diode (LED).10. The apparatus of claim 1, wherein the at least one photodetectorgenerates optical tissue data that comprises data which is used by oneor both of the processor and a processor of an electronic device tocalculate one or more of hydration index, oxygenated hemoglobinconcentration, deoxygenated hemoglobin concentration, total hemoglobinconcentration, hemoglobin index, hemoglobin concentration index, lactatethreshold, and ventilatory threshold.
 11. A biometric recognitiondevice, comprising the apparatus of claim 1, wherein the biometricrecognition device is configured for detection and identification ofdifferent subjects.
 12. A system operable to optically detect tissue,the system comprising: a tissue detection device comprising: at leastone light source operable to emit light of at least three wavelengthsinto a material, at least one of the at least three wavelengths beingabout 980 nanometers; and at least one photodetector operable to detectat least a portion of the light reflected from the material; and anelectronic device coupled to the tissue detection device and operable totransmit signals to activate the at least one light source and receivedata from the at least one photodetector, the electronic devicecomprising: a non-transitory medium coupled with a processor and storinginstructions for determining whether the material is a biological tissueof a subject or a non-tissue material and for launching an activity whenthe material is the biological tissue; and the processor coupled withthe at least one light source and the at least one photodetector, theprocessor operable to execute the instructions, stored in thenon-transitory medium, for: determining whether the material is thebiological tissue or the non-tissue material based on the light detectedby the at least one photodetector, when the material is the biologicaltissue, launching the activity, wherein the activity includes the atleast one photodetector recording measurements, and the non-transitorymedium is operable to store the recorded measurements, and when thematerial is the non-tissue material, not launching the activity, andinitiating an alert by an output device to check placement of theapparatus, wherein the at least one light source emits light atpredetermined intervals to determine if the at least one photodetectoris proximate to the tissue, and wherein the at least one light sourceand the at least one photodetector are operable to be enabled by furtheractivation, wherein the further activation includes the processordetecting a movement.